ÉCOLE POLYTECHNIQUE PROMOTION X 2007 BORELY Olivier olivier.borely@polytechnique.edu

RESEARCH INTERNSHIP REPORT RAPPORT DE STAGE DE RECHERCHE

Analysis of United States west coast upwelling winds and climatology from the 20th Century

Reanalysis project

RAPPORT NON CONFIDENTIEL

Mécannique et Physique pour l’Environnement Directeurs de l’option : Hervé Le Treut, Jean-François Roussel et Thomas Dubos Directeur de stage : Nathan J. Mantua 12 Avril 2010 – 25 Juin 2010 Climate Impacts Group 3737 Brooklyn Ave. NE PO Box 355672 Seattle, WA 98195 USA

Contents

Abstract 1

1 Climatic context of west coastal United States during summerand future evolutions 31.1 Climatic context of west coastal United States . . . . . . . . . . 3

1.1.1 Pressure Gradient . . . . . . . . . . . . . . . . . . . . . . 31.1.2 Temperature inversion . . . . . . . . . . . . . . . . . . . . 31.1.3 Upwelling . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.2 Consequences of global warming . . . . . . . . . . . . . . . . . . 71.2.1 Bakun’s hypothesis . . . . . . . . . . . . . . . . . . . . . . 71.2.2 Consequences of enhanced upwelling . . . . . . . . . . . . 7

2 Summer mean analysis 92.1 Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1.1 Several datasets . . . . . . . . . . . . . . . . . . . . . . . 92.1.2 Accuracy of the 20th Century Reanalysis Dataset . . . . . 9

2.2 Summer trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2.1 Wind . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2.2 Land Temperature . . . . . . . . . . . . . . . . . . . . . . 132.2.3 Sea temperature . . . . . . . . . . . . . . . . . . . . . . . 152.2.4 Pressure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.2.5 Thermal Inversion . . . . . . . . . . . . . . . . . . . . . . 202.2.6 Discussion of Bakun’s theory . . . . . . . . . . . . . . . . 20

2.3 Interaction between wind and Temperature . . . . . . . . . . . . 212.3.1 In the west coastal United States . . . . . . . . . . . . . . 212.3.2 Other upwelling regions . . . . . . . . . . . . . . . . . . . 24

3 Analysis of daily summer variability 273.1 Sea-land contrast . . . . . . . . . . . . . . . . . . . . . . . . . . . 273.2 Interaction between wind and temperature . . . . . . . . . . . . . 28

4 Discussion 31

Bibliography 32

List of Figures 35

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Abstract

An increase in alongshore wind off Californian coasts during summer monthshas been observed and documented during the 20th century, and has been con-nected to global warming. This report focuses on the linear trends in severalclimatic quantities, including temperature, sea level pressure, meridional windand inversion strength, using the 20th Century Reanalysis Dataset. It appearsthat over land, coastal locations have warmed faster than inland locations, lead-ing to a decrease in temperature gradient between coast and land. It comes withan increase in sea surface temperature, and a decrease in sea surface pressureand in inversion strength off central and southern California. A model has beenproposed: the North Pacific High seems to have gradually retracted duringthe 20th century. The subsidence of warm air over the marine boundary layeris thus less strong, and the inversion strength decreases. The marine bound-ary layer is thicker, and when the inversion is higher than coastal topography,marine air can drip over the coastal ranges, carrying with it moisture and cloudi-ness. Clouds over land reduce the incoming solar radiation amount, producingcool conditions inland, while warmer and dryer conditions predominate in thecoastal area. Several issues can be pointed out, such as the documented increasein upwelling-favorable winds, which does not match this scenario, and the pooraccuracy of the 20th Century Reanalysis compared to observational measures.

Une augmentation pendant les mois d’été du vent parallèle aux côtes deCalifornia centrale et méridionale a été observée et documentée sur l’ensembledu XXe siècle . Cette augmentation a été reliée au réchauffement climatique.Ce rapport examine différentes grandeurs climatiques, parmi lesquelles la tem-perature, la pression au niveau de la mer, le vent méridionnal et l’intensité del’inversion, et tente de déterminer leurs tendances au premier ordre, en se ba-sant sur la base de données de la 20th Century Reanalysis. Il apparaît que surterre, la zone cotiêre s’est réchauffée plus rapidement que l’intérieur des terres,conduisant à une réduction du gradient de température entre la côte et l’inté-rieur du continent. Cette décroissance est accompagnée d’une élévation de latempérature à la surface de la mer, et d’une diminution de la pression au niveaude la mer, ainsi que d’une réduction de l’intensité de l’inversion thermique aularge des côtes de Californie centrale et méridionale. Un modèle simplifié per-met d’expliquer ces tendances : une rétraction de l’anticyclone Nord Pacifiqueau cours du XXe siècle pourrait etre à l’origine de ces évolutions. Elle auraitconduit à une réduction de l’intensité de la subsidence d’air chaud au-dessusde la couche limite marine, et donc à une inversion thermique moins intense.La couche limite marine gagne en épaisseur et, lorsque la hauteur de l’inversiondépasse la topographie côtière, l’air marin peut franchir les massifs côtiers, em-portant dans son flot nuages et humidité. Le rayonnement solaire incidant estécranté par la présence de nuages, avec pour conséquences, des températuresfraîches a l’intérieur des terres et des températures plus chaudes et un air plussec au niveau des côtes. L’étude compte plusieurs imperfections. L’augmentationconstatée de l’intensité de l’upwelling ne correspond pas au scénario proposé, etla qualité de la base de données de la 20th Century Reanalysis est très discutableau regard de mesures expérimentales directes.

AcknowledgmentsI would like to thank Dr. Nathan J. Mantua for his direction, assistance, andguidance.

I also wish to thank John M. Wallace, Todd P. Mitchell, James A. Johnstone,Guillaume S. Mauger and Karin A. Bumbaco, for their support and for theirrecommendations and suggestions which have been invaluable for this project.

I am also thankful towards the Joint Institute for the Study of the Atmo-sphere and Ocean and towards the Climate Impacts Group, where I have spentthree months working in nice conditions.

I would like to acknowledge the many people who have made it possible forme to have this internship, especially my teachers at the Ecole Polytechnique,Hervé Le Treut, Jean-François Roussel and Thomas Dubos, as well as FrancisCodron.

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Chapter 1

Climatic context of westcoastal United Statesduring summer and futureevolutions

1.1 Climatic context of west coastal United States

1.1.1 Pressure GradientEastern ocean boundary regions are among the most productive areas in theworld, characterized by strong wind-driven upwelling of cold, nutrient-rich wa-ters. From late spring to early fall, the west coast of the United States andadjacent Pacific Ocean are under the influence of persistent southward winds,inducing strong upwelling alongshore.

The near-surface air flow over the eastern North Pacific is the result of acomplex sea-atmosphere-land pattern.

The North Pacific is dominated by the North Pacific High, a subtropicalanticyclone lying approximately at 38◦N, 150◦W, whereas relatively low pressureprevails over the southwestern United States deserts (c.f. Figure 1.1.1). Itcreates a Sea Level Pressure gradient between land and ocean, which drivespersistent southward winds over the coastal ocean.

1.1.2 Temperature inversionThe temperature structure over the Northeast Pacific Ocean is characterized bya marked inversion during the warm season, of the order of 10◦C in potentialtemperature. The subsidence associated with the North Pacific High, coupledwith a turbulent mixed marine layer, helps to maintain and strengthen thisinversion [Neiburger, 1960].

The inversion acts as a lid on the upward transport of water vapor. Abovethe inversion, the air is very dry and warm. It may be reinforced by west-ward advection of hot dry air from the continent. Below the inversion, in the

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Figure 1.1: Mean summer sea level pressure between 1908 and 2006 (data from20th Century Reanalysis dataset)

Figure 1.2: Average summer cross section from San Francisco to Honolulu (from[Neiburger et al., 1961])

turbulent, well-mixed marine layer, the air is cool and quite moist.Baroclinicity from the horizontal temperature gradient between relatively

cool ocean surface and warm heated continent causes the inversion to slopedownward toward the coast, with enhanced wind speed adjacent to the coast.The inversion has a mean height of the order of 400 m along the central andnorthern California coast. It rises quickly in the westward direction for the first200 km, then more slowly to reach an elevation of the order of 2000 m aroundHawaii. (cf Figure 1.1.2)

According to the conceptual and descriptive model of [Beardsley et al., 1987],we can divide the coastal ocean in 3 zones.

In the offshore zone, the marine inversion tilts slowly down towards the coast.This eastward tilts reflects the effect of the subsidence of the subtropical highin the eastern North Pacific in summer. The surface southward winds are of theorder of 5 to 7.5 m/s.

In the intermediate zone, from 20 km to 200 km, the marine boundary layertilts more steeply toward the east. This sharper sloped inversion base comeswith an enhanced baroclinicity, and a faster surface flow, with a maximum offnorthern California coast, where average winds reach 10 m/s.

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Figure 1.3: Conceptual model of average lower atmosphere over eastern NorthPacific during periods of persistent south and southeastward winds in summer(from [Beardsley et al., 1987])

Figure 1.4: Conceptualmodel of average loweratmosphere over thenearshore zone dur-ing (top) night and(bottom) day. (from[Beardsley et al., 1987])

In the nearshore zone, the surface flow is charac-terized by a strong land-sea diurnal variability. Atnight, the wind is strong southward at 20 km off-shore, and decreases towards shore, where the loweratmosphere has been cooled during the night. Dur-ing the day, the sun heats the land surface, changingthe stable air over the coast to unstable. The air be-low the inversion penetrates onshore, which resultsin an acceleration of the winds over the beach, andin a depression of the nearshore inversion. Duringthe day the inversion tilts downward to a minimumelevation (of the order of 50-100 m) just over thebeach. Inland, the inversion lifts very slowly andbecomes very diffuse.

The climatology of this region is further com-plicated by a wide variety of mesoscale circulationsand coastal trapped events, particularly during thesummer. Meso-scale climate zones and circulationare determined by the interaction between the coolsynoptic-scale flow from the marine boundary layerand the various mountain ranges, valleys and passes.

The Pacific mountain system form an easternobstacle to the expansion of the marine boundarylayer. This system are the series of mountain rangesthat stretch along the West Coast of North Americafrom Alaska south to Northern and Central Mexico.

Occasionally, coastally trapped events occur that cause the inshore inversionto be lifted. If the inversion remains lower than the prevailing topography of

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the Coast Ranges, inland penetration of marine air is thus limited to a low-elevation coastal zone, with an interior boundary defined by the inversion heightand the local relief. Clouds within the moist, cool marine boundary layer arethus sequestered in coastal area, often evolving into fog. Areas located at thewest of the Coastal Ranges enjoys an exotic wet climate, while eastern area areextremely dry and warm.

The inland penetration of the marine boundary layer induces a strong con-trast in daily temperature, which differs by nearly 20◦C between coastal andinland locations.

1.1.3 Upwelling

Those southward alongshore winds produce strong upwelling in the coastal area.Near-surface water is transported farther offshore through Ekman pumping, andis replaced with cold and salty water full of nutrients from the depths below.Along with dissolved CO2 and light energy from the sun, those nutrients areused by phytoplankton to produce organic compounds, through the process ofphotosynthesis.

Very high levels of primary production (the amount of carbon fixed by phyto-plankton) result from these specific conditions. High primary production prop-agates up the food chain following the course of [Mann and Lazier, 2006]:

Phytoplankton→ Zooplankton→ Predatoryzooplankton→ Filterfeeders→ Predatoryfish

Other evidences of the intense upwelling are the bending of isotherms south-

Figure 1.5: A conceptual diagram of the coastal upwelling process [fromwww.nwfsc.noaa.gov]

ward along the coast, producing sea surface temperatures 4◦C lower than atcomparable latitudes in the open Pacific, and lowering of alongshore sea-level,of about 0.1-0.2 m during upwelling events.

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1.2 Consequences of global warming

1.2.1 Bakun’s hypothesisThe large scale of these pressure systems makes them sensitive to climate vari-ability. The long-term increase in upwelling has been observed and well docu-mented in coastal California since the mid 20th century [Bakun, 1990, Garcia-Reyes and Largier, 2010].It has been suggested that global warming would be responsible for this increase.[Bakun, 1990] proposed that global greenhouse warming

should lead to intensification of the continental thermal lows adja-cent to upwelling regions. This intensification would be reflected inincreased onshore-offshore atmospheric pressure gradients, enhancedalongshore winds, and accelerated coastal upwelling circulation.

As the earth warms, the land warms faster than the ocean. The land-sea tem-perature difference is thus expected to increase, with the associated land-seapressure gradient, leading to stronger alongshore winds and thus enhancedcoastal upwelling. Analysis of wind time series along the coast of Californiahave indeed confirmed the increase in alongshore wind speed [Bakun, 1990,Garcia-Reyes and Largier, 2010, Schwing and Mendelssohn, 1997, Mendelssohn and Schwing, 2002]Numerical models have confirmed that increased global temperature would leadto stronger winds along the coast [Snyder et al., 2003, Auad et al., 2006]. Theconsequences of such intensification in the upwelling-favorable winds have re-ceived considerable attention in the past decade.

1.2.2 Consequences of enhanced upwellingEnhanced upwelling is expected to cool waters over the shelf, while further off-shore, an increase in surface heating can be expected to exceed the cooling ef-fects of increased upwelling. The effects are further complicated by other changein oceanographical conditions, such as the deepening of the level of the ther-mocline and changes in the thermal stratification [Palacios et al., 2004]. Thestrength of the upwelling affects the amount of primary production available,and the amount delivered to coastal ecosystems rather than offshore ecosys-tems. Since 1951, the biomass of macrozooplankton in waters off southernCalifornia has decreased by 80 percent [Roemmich and McGowan, 1995]. En-hanced upwelling would push surface water away from the coast more rapidly,resulting in less phytoplankton availability in coastal waters and a greaterbut more diffuse supply of phytoplankton to waters over the outer shelf andslope, while enhanced surface heating reduces phytoplankton availability fur-ther offshore[Botsford et al., 2003, Botsford et al., 2006].

Upwelling intensification could result in dramatic consequences on the bio-logical cycles in the coastal zone. Furthermore, it would have a human impact,by rising the sea level, threatening Californian beaches, with an important eco-nomic impact [Pendleton et al., 2006]. Tourism and fisheries would also sufferfrom a change in climatic conditions, as spotted by [Cooley and Doney, 2009].

Expanding job losses and indirect economic costs will follow harvestdecreases as ocean acidification broadly damages marine habitatsand alters marine resource availability. Losses will harm many re-gions already possessing little economic resilience.

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Thus, climate change would have a dramatic economic impact.

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Chapter 2

Summer† mean analysis

2.1 Datasets

2.1.1 Several datasetsThe Twentieth Century Reanalysis (V2) data are provided by the NOAA/OAR/ESRLPSD, Boulder, Colorado, USA, from their Web site at www.esrl.noaa.gov/psd/.This is a reanalysis dataset spanning 1871 to present, assimilating only sur-face observations of synoptic pressure, monthly sea surface temperature andsea ice distribution. It provides the first estimates of global tropospheric andstratospheric variability at six-hourly resolution. It has a two degree longitude-latitude horizontal resolution, which corresponds approximately to a 150km-220km zonal-meridional resolution in the North Pacific.

Daily direct observations measurements are also available at stations allover the United States. Those data are gathered in the United States His-torical Climatology Network (USHCN). The USHCN is a data set of daily andmonthly records of basic meteorological variables from observing stations acrossthe United States. To conduct further analyses of the climate of the westernUnites States area, only the 114 stations located in California and in the westpart of Oregon and Washington states have been used.

The USHCN stations are located inland. To study climatic features overthe ocean, data from 15 buoys of the National Data Buoy Center (NDBC) havebeen used. Available measures are more scattered than for the USHCN stations.There are a lot of missing days, and it is difficult to find continuous time series ofmore than 20 years. We selected the buoys for which the available data coveredthe longest time frame.

2.1.2 Accuracy of the 20th Century Reanalysis DatasetTo discuss the reliability of the 20th Century Reanalysis Dataset, correlationscoefficient are computed between mean summer temperature for each of the114 west coast USHCN stations between 1908 and 2006 and the mean summertemperature at sigma level 0.995 for the same locations and same time frame

†In all this section, the term summer refers to the period between June 1st and September30th

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given by the 20th Century Reanalysis Dataset. The correlation coefficient foreach station is plotted on 2.1.

0.1

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Figure 2.1: Correlation of mean summer (JJAS) temperature between the20thCentury Reanalysis Data and the USHCN Data, from 1908 to 2006

It appears clearly that the correlation between the observations at the USHCNstations and the reconstructed temperature of the 20th Century Reanalysis arenot very conclusive. The mean correlation is 0.4, and the value are widely dis-tributed around the mean (standard deviation = 0.12). One can notice that thestations located along the south coast of the area are less correlated with the20th Century Reanalysis data than those located further inland. It is probablydue to the fact that summer climate in this area is modulated by local topogra-phy. The resolution of the 20th Century Reanalysis is too coarse to detect thosevery local patterns. Especially along the coast, cooler temperature is observedfrom the beach to the Coast Ranges, within an area of a few dozens of kilome-ters. The 20th Century Dataset has a spatial resolution of about 160 km andcan’t detect this local pattern.

The mean summer meridional wind value from the 15 NDBC buoys arecompared with the value of the meridional wind at the same locations from the20th Century Reanalysis dataset, between 1983 and 2006. The correlation arecalculated for each of the buoys, and displayed on 2.2

The meridional wind from the 20th Century Reanalysis over the ocean isbetter correlated with NDBC data. The mean correlation is 0.57, but the valueare more widely distributed (standard deviation = 0.24). Data are not verywell correlated along the Californian coast, certainly because the buoys arelocated over the continental shelf over this area, where the wind is affected bycoastal topography on a small scale. Further offshore, wind from 20th CenturyReanalysis is rather well correlated with observations from the buoys.

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Figure 2.2: Correlation of mean summer (JJAS) meridional wind between the20thCentury Reanalysis Data and the NDBC Data, from 1908 to 2006

2.2 Summer trends

2.2.1 Wind

Literature review

[Bakun, 1990] published a controversial paper, documenting an intensification ofthe alongshore wind stress off western United States, from 30◦N to 48◦N duringthe spring-summer season. It established a link between global warming and thisescalation of alongshore winds. He calculated 40 years of upwelling index derivedfrom atmospheric pressure records at several locations along the west coast ofNorth America from the 1940’s to the 1990’s. [Schwing and Mendelssohn, 1997]found also an increase in alongshore wind stress between 32◦N and 40◦N duringApril-July from 1946 to 1990. They used quality-controlled reports of oceansurface conditions, mostly taken by ships-of-opportunity. The key to identifythe strengthen wind stress was the ability to separate the long-term nonlineartrend, using the state-space models [Shumway, 1988, Harvey, 1989], which maskthe signal of increased upwelling in the observations.

Those studies have focused on spatial scales larger than that of the coastalupwelling process, which typically occurs over the continental shelf within 10km off the shore in intense and localized upwelling zones [Capet et al., 2004].[Bakun, 1973] used a 3-degree mesh length geographical grid, which means 230km width squares at 45◦N, and [Schwing and Mendelssohn, 1997] used spatialregions of approximately 2◦latitude by 4◦ longitude, which means 150 km wideat 45◦N.

The most recent publication addressing this phenomenon is by [Garcia-Reyes and Largier, 2010].They observed an increase in the upwelling-favorable winds in Central Califor-nia (35◦N-39◦N) during the upwelling season (March-July). They use 27 years(1982-2009) of hourly data on winds over the shelf, which are available frombuoys deployed by the National Data Buoy Center (NDBC).

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Using the datasets

We used the available datasets to compute the trends of the meridional windoffshore in the area.

?

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Figure 2.3: Mean linear trend of mean NDBC summer meridional wind, from1983 to 2009. The ? represent the stations for which no linear trend can be observed witha confidence level higher than 95% (P<0.051)

NDBC buoys The linear trend in mean summer southward meridional windat each of the NBDC buoys have been computed for 27 years, from 1983 to2009. The buoys for which the sign of the linear trend is sure with a 95%confidence level (P<0.051) are displayed in Figure 2.3. Consistant with thework of [Garcia-Reyes and Largier, 2010], only the buoys located in a nearshorearea along central California coasts show a significant increase trend, of about2 m.s−1/century. For the other locations, no significant trend can be observed,neither positive nor negative. The increase of wind speed alongshore off centralCalifornia is consistent with the theory of increase upwelling caused by globalwarming. However, we do not have time series long enough to make a conclusion,all the more so even within the 27 years of the analysis, there are a lot of missingvalues.

20th Century Reanalysis Data The linear trend in the 20thCentury Re-analysis wind are computed for summer between 1908 and 2006. The 95%confidence level (P<0.051) values are displayed in Figure 2.2.1 for the meansummer southward meridional wind at sigma level 0.995.

For the meridional wind, we notice an increase in the speed only for 3 gridpoints, off central California, consistent with an increase of upwelling-favorablewinds in this area. The mean linear slope is 0.7 m.s−1/century. Even if the20th Century Reanalysis Data are not as accurate as observational data, itcorroborates the observations of NBDC from 1983 to 2009, in which an increasein temperature was only observable off central California. It seems that thisincrease is not just an effect of wind fluctuation, but a real trend that we findall over the century.

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Figure 2.4: Mean linear trend of mean 20th Century Reanalysis summer south-ward meridional wind at sigma level 0.995, from 1908 to 2006. Only are representedthe grid points where the sign of the linear trend is sure at the 95% confidence level (P<0.051)

2.2.2 Land Temperature

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Figure 2.5: Mean linear trend of mean USHCN summer average temperature,from 1908 to 2006. Only are plotted the stations for which the sign of the linear trend issure at the 95% confidence level (P<0.05 1)

In Figure 2.5, the slope in long term summer mean temperature for eachof the 114 USHCN stations have been computed. Only are displayed the sta-tions for which the sign of the linear trend is sure at the 95% confidence level(P<0.051). The global trend is an increase in mean summer temperature foreach of the stations except one, the mean slope being of 1◦C/ century. Thisincrease is consistent with the well-known phenomenon of global warming. Nospecial pattern in the increase in mean summer temperature can be read on thisfigure.

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Coast - Inland contrast

Following previous studies [Johnstone and Dawson, 2010], a principal compo-nent analysis was performed with the correlation matrix of the 114 USHCNstations of the area, for the summer mean Tmax records from 1908 to 2006.The western boundary of the spatial domain was defined by the U.S. Pacificcoastline, and the eastern margin was delimited by the eastern boundary ofCalifornia and by the 120◦W longitude line in Oregon and Washington, whichcontinues the California boundary northward. This area covers approximatelythe first 300 km of the U.S. Pacific coastal region. All stations within this areawere used in the analysis.

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(a) The correlation between the temperature time series of each station and the

time series of the corresponding principal component are represented

1950 2000−3

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Figure 2.6: The three first principal component of the mean summer air tem-perature from the 114 western U.S. USHCN stations

The maps of the correlation between TMAX and its three first PC are rep-resented in Figure 2.6(a).TMAX PC 1 captures 42% of total interannual variance and reflects coherent

variations over nearly the entire region, with all stations but one sharing PCloadings of the same sign. Santa Cruz is the sole exception, with a loadingslightly below zero. The PC 1 time series is virtually identical to the unweightedmean of all 114 stations records (r>0.99).

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TMAX PC 2 accounts for 12% of variance and captures a north-south con-trast.TMAX PC 3 explains 10% and primarily reflects a coast-interior contrast. It

appears that TMAX PC 3 has a pronounced increase trend. Further analyseshave been performed to discuss the physical relevance of this mode.

The regional PC 3 series can be exemplified (r=0.72) by the TMAX differencebetween time series from San Luis Obispo, CA, located in coastal southernCalifornia, in an area fully exposed to marine air penetration, and Orland, CA,located in the Northern California Coast Range interior, (cf Figure 2.2.2).

Figure 2.7: Map of United States West Coast. The stations of Orland and ofSan Luis Obispo are represented

Thus, this third mode of the Principal Component Analysis of mean summerTMAX accounts for the temperature contrast between coastal locations andinland locations. An analysis of the time series of San Luis Obispo (coastallocations) and of Orland (inland locations) makes it clear that, when the TMAXPC3 increases, the temperature contrast decreases, and inversely, when TMAXPC3 decreases, the temperature contrast increases.

As during the 20th century, TMAX PC3 has increased, it means that the tem-perature gradient has decreased. Indeed, coastal stations temperature (EOF3>0)have increased by 1.36◦C/century, whereas inland stations temperature (EOF3<0)have only increased by 0.94◦C/century.

2.2.3 Sea temperatureAt last, the linear trend in the 20th Century Reanalysis Data are computedfor 1908 to 2006. The 95% confidence level (P<0.051) values are displayed inFigure 2.2.3 for the mean summer Temperature at sigma level 0.995.

An increase in temperature over ocean is apparent in this Figure 2.2.3. Theaverage increase is of 0.7◦C/century, with an extreme value of 1.45◦C/centuryoff Southern California. There is no discernible increase in temperature overland in this dataset. As we have seen above (2.1.2, page 10), data from thereconstructed 20th Century Reanalysis data are not very well correlated with

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Figure 2.8: Mean linear trend of mean 20th Century Reanalysis summer tem-perature at sigma level 0.995, from 1908 to 2006. The grid points where the sign ofthe linear trend is not sure at the 95% confidence level (P<0.051) are represented in green

USHCN data. We can assume that this reconstructed dataset does not capturethe real evolution of land temperature. It would account for the lack of notice-able increase in temperature over land. However, as the dataset is built usingobservations of monthly sea surface temperature (c.f. 2.1.1, page 9), the valueof sea surface temperature should be relevant.

Thus, an increase in temperature is observable all over the ocean, especiallyover the waters off central and southern California, where it goes with an in-crease in southward alongshore wind speed.

The TMAX PC 3 time series is also correlated (r=0.69) with Sea SurfaceTemperature offshore Southern California, as we can see in Figure 2.2.3. Theincrease in sea surface temperature seems to be connected with the decrease intemperature contrast between coast and land.

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l 0.9

95

Figure 2.9: Mean sea surface temperature at (32◦N,122◦W) and the PC3 ofTMAX

16

2.2.4 PressureThe sea level pressure from the 20th Century Reanalysis have also been analyzed.We used mean summer pressure at sigma level 0.995 to calculate the time seriesof pressure from 1908 to 2006. The linear slope is shown on Figure 2.2.4 forlocations where the confidence level is superior to 95%. The mean slope is -228Pa/century. The data should be accurate over ocean, as the dataset is builtwith synoptic pressure records. Thus, there is a decrease trend off central andsouthern Californian coasts. As we can see on Figure 2.2.4, the low pressuresystem located over south-western United States has extended during the 20th

Century, leading to a retraction of the North Pacific High further offshore.

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

−4

−3

−2

−1

0

1

2

3

4

Figure 2.10: Mean linear trend of mean 20th Century Reanalysis summer pres-sure at sigma level 0.995, from 1908 to 2006. The grid points where the sign of thelinear trend is not sure at the 95% confidence level (P<0.051) are represented in green. Theunits of the colorbar are Pa/an

The correlation between PC3 of TMAX and Sea level Pressure from the 20th

Century Reanalysis have also been computed for the mean summer value, from1908 to 2006. The results are shown in Figure 2.12(a). The Sea level Pressure isnegatively correlated with the PC3 of TMAX in the whole area. The correlationis most negative offshore California. The most negative correlation is of -0.59,and is reached at (32◦N,118◦W). Both PC3 of TMAX and mean summer sea levelpressure are plotted on Figure 2.12(b). The sea level pressure at this locationhas a negative liner trend of -346 Pa/century.

Thus, the decrease in sea level pressure seems to be also connected with thereduced temperature contrast between coastal and inland locations.

17

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

101500

1015

00

1015

00

1020

00

102000

102000

(a) 1908-1940

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

101500

1015

00

1015

00

102000102000

102000

(b) 1941-1973

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

101000

101500

1015

00

1015

00

1020

00102000

102000

(c) 1974-2006

Figure 2.11: Mean summer (JJAS) Sea Level Pressure, from 1908 to 2006 Thepressure difference between 2 isobars is 100 Pa

18

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

−0.5

−0.4

−0.3

−0.2

−0.1

0

(a) Correlation between the TMAX PC3 and sea level pressure, formean summer time series between 1908 and 2006

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

−10

−8

−6

−4

−2

0

2

4

6

8

10

Multiple Decay Rates

Year

PC

3 of

SLP

1910 1920 1930 1940 1950 1960 1970 1980 1990 20001.009

1.01

1.011

1.012

1.013

1.014

1.015

1.016x 10

5

Sea

Lev

el P

ress

ion

(b) PC3 of TMAX ans mean summer sea level pressure at(32◦N,118◦W)

19

2.2.5 Thermal InversionThis PC 3 time series displays a good correlation (0.68, cf 2.2.5) with the Tem-perature difference between pressure level 850 mbar and 950 mbar (Δ T) overSouthern California (32◦N,116◦W). This temperature difference is computedusing mean summer value of atmospheric temperature from the 20th CenturyReanalysis dataset, and is an index of the strength of the inversion.

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000−10

−8

−6

−4

−2

0

2

4

6

8

10Multiple Decay Rates

Year

Tm

ax P

C3

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000−4.5

−4

−3.5

−3

−2.5

−2

Tem

pera

ture

diff

eren

ce b

etw

een

850

and

950

mb

Figure 2.12: Temperature difference between 850 mbar and 950 mbar at(32◦N,116◦W), and TMAX PC3 (inverted)

2.2.6 Discussion of Bakun’s theoryFrom these analyses, we can conclude that contrary to [Bakun, 1990]’s expecta-tions, the temperature gradient between coast and land has not increased duringthe 20th century, but decreased. The temperature at the stations located in thecoastal area has increased by 1.36◦C/century, whereas for those located inland,the temperature has only increased of 0.94◦C/century. It seems to be connectedwith a gradual retraction of the North Pacific High, indicated by the decrease ofsea level pressure off central and southern California. The strong subsiding airis thus located further offshore, which result in a more diffuse marine boundarylayer alongshore. As it is suggested by the decrease in temperature differencebetween pressure level 850 mbar and 950 mbar, the inversion has weakened. Thesea level temperature, as well as the coastal air temperature has risen. It can beexplained by the decrease of cloud cover over the coastal area, inducing warmercondition because of more incoming solar radiation, while further inland, thoseclouds and moist results in cooler conditions.

20

2.3 Interaction between wind and Temperature

2.3.1 In the west coastal United StatesThe simple scenario proposed above in 2.2.6, page 20, is not consistent withthe observed increase of alongshore southward upwelling-favorable winds duringthe 20th century. The thickening of the marine boundary layer should resultin weaker winds alongshore within the marine boundary layer. The reversephenomenon is observed, as the alongshore winds increase.

[Bakun, 1990] had proposed that the increase in temperature contrast shouldinduce stronger winds. To address this hypothesis, we have focused on theinteraction between wind and temperature contrast.

The correlation between TMAX PC3 and southward alongshore meridionalwind have been computed for each of the 2◦-length squares of the 20th CenturyReanalysis. The results are displayed in 2.3.1. However, no significant corre-lation can be observed. The maximum correlation is reached offshore southernCalifornia, but remains very low (r=0.28). The lack of correlation might beconnected to the multiple time scales which interfere in wind variability.

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Figure 2.13: Correlation between mean summer southward meridional wind andthe PC3 of TMAX

In order to capture a better picture of the interactions between wind variabil-ity and temperature variability in the area, an Singular Value Decomposition(SVD) of both fields in the area has been performed, with the cross-covariancematrix of the mean summer TAVE value for each of the 114 USHCN stationslocated along the U.S. West Coast from 1908 to 2006 on the one hand, and ofthe mean summer southward meridional wind between meridians 132◦W and116◦W, and parallels 32◦N and 48◦Non the other hand. We focus on the secondmode of this analysis, which explains 22% of total squared variance. Relevantfigures are displayed in 2.3.1.

It appears that the second mode of the SVD analysis for TAVE exhibits acontrast between coastal and inland locations. There is a slightly linear in-crease trend, but its confidence level is lower than 80%. This second mode is

21

rather well correlated (r=0.7) with the PC3 of TMAX of the PC analysis. Thecorrelation between the second mode for temperature and for wind is 0.47 (cfFigure 2.14(c)). There is a light positive correlation (r=0.2) between wind andTAVE second mode over central California, but the principal area where thewind is strongly correlated with the TAVE second mode is off Oregon coasts,with a maximum correlation at (44◦N,126◦W) (r=-0.55). The second mode ofthe meridional wind shows no significant linear trend.

The area where the variability in upwelling-favorable alongshore winds isbest explained by the variability in the temperature gradient between coast andland is thus located off the Oregon coasts. However, even if the variabilitymode for the temperature contrast shows a linear slope, it is not combined withan increase for the associated mode in wind. The correlation might only beenlinked to the local maximum of southward wind off Oregon shore, and not to aphysical interaction of both physical data.

22

(a) Correlation between Temperature and its Second Mode

−130 −125 −12032

34

36

38

40

42

44

46

48

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

0.4

0.5

(b) Correlation between southward meridional wind and tempera-ture second mode

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

0

US

HC

N T

ave

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

0

Mer

idio

nal V

−W

ind

(c) Wind and Temperature second modes: The second mode ac-counts for 22% of total squared variance. Correlation betweenthe two modes: r=0.47

Figure 2.14: Results of the Singular Value Decomposition of the mean sum-mer (JJAS) temperature from the 114 USHCN stations and of the southwardmeridional wind, between 1908 and 2006

23

2.3.2 Other upwelling regions[Bakun, 1990] also pointed out that upwelling-favorable wind stress had notincreased only off Californian coastline, but also in other the other major sub-tropical eastern ocean boundary regions, such as the Canary current system offthe Iberian Peninsula and northwestern Africa, the Benguela current system offsouthwestern Africa, and the Peru current system off western South America.The upwelling in those regions is induced by the same type of synoptic patternthan in the coastal ocean off the western United States: a strong atmosphericpressure gradient between warm heated land and an the higher pressure overthe ocean that drives vigorous alongshore equatorward wind. As the synopticpatterns are the same in those region than in the eastern United States, anincrease in land temperature should also lead to an increase upwelling. Bakuncomputed the linear trend of alongshore wind stress in those regions, from the1940’s to the late 1980’s. We have conducted the same kind of analysis withthe 6-hour daily meridional wind values from the 20th Century Reanalysis, forthe same frame of time but also for a longer period, to determine if a trendcan be observed during the 20thcentury. The wind stress is computed using6-hour-daily meridional wind data, using the same classical square-law formulathan [Bakun, 1973]

�τ = ρaCd |�v|�vwhere �τ is the stress vector, ρa is the density of air(1.22kg/m3), Cd is an em-pirical drag coefficient, �v is the estimated wind vector near the sea surface withmagnitude |�v|. A relatively high value, 0.0026, of the drag coefficient was usedto partially offset the effect of using mean data. The linear slope was determinedby the method of least square.

In each area, an increase trend can be noticed. However, as we have pointedout above, the increase trend off California is not significant. In the otherarea, the trend is significant at 95% for the period between 1946 and 1988,and significant at 99% for Spain, Morocco and summer in Peru for the periodbetween 1908 and 2006. Bakun’s theory seems to be more relevant in thosearea, even if further investigations should be conducted, first of all to confirmthe accuracy of the wind data from the 20th Century Reanalysis.

California is the upwelling region where the alongshore wind has less in-creased during the 20th century. This is thus the region where Bakun’s hypoth-esis is the less likely to be verified. That might be the reason why we concludedthat Bakun’s theory was not accurate for this region.

24

(a) From [Bakun, 1990],slope=0.0206**

1950 1955 1960 1965 1970 1975 1980 19850.8

11.21.41.61.8

dyne

/cm

2

(b) From 20th C.R.,slope=0.0021

1920 1940 1960 1980 20000.60.8

11.21.41.61.8

dyne

/cm

2

(c) From 20th C.R.,slope=0.0008

Figure 2.15: Alongshore April to September wind stress off California, (a) from1946 to 1988, (39◦N,125◦W), (b) from 1946 to 1988, (38◦N,124◦W), (c) from1908 to 2006, (38◦N,124◦W) [significance: * = P < 0.05; ** = P < 0.011], wind stress is in dyne/cm2

(a) From [Bakun, 1990],slope=0.0033**

1950 1955 1960 1965 1970 1975 1980 19850

0.5

1

dyne

/cm

2

(b) From 20th C.R.,slope=0.0056*

1920 1940 1960 1980 20000

0.5

1

dyne

/cm

2

(c) From 20th C.R.,slope=0.0034**

Figure 2.16: Alongshore April to September wind stress off Spain, (a) from 1946to 1981, (43◦N), (b) from 1946 to 1988, (42◦N,10◦W), (c) from 1908 to 2006,(42◦N,10◦W) [significance: * = P < 0.05; ** = P < 0.011], wind stress is in dyne/cm2

(a) From [Bakun, 1990],slope=0.0174**

1950 1955 1960 1965 1970 1975 1980 1985

0.81

1.2

dyne

/cm

2

(b) From 20th C.R.,slope=0.0031*

1920 1940 1960 1980 20000.60.8

11.21.4

dyne

/cm

2

(c) From 20th C.R.,slope=0.0019**

Figure 2.17: Alongshore annual wind stress off Morocco, (a) from 1946 to1981, (28◦N), (b) from 1946 to 1988, (28◦N,22◦W), (c) from 1908 to 2006,(28◦N,22◦W) [significance: * = P < 0.05; ** = P < 0.011], wind stress is indyne/cm2

25

(a) From [Bakun, 1990],slope=0.0035**

1950 1955 1960 1965 1970 1975 1980 19850.5

1

dyne

/cm

2

(b) From 20th C.R.,slope=0.0059**

1920 1940 1960 1980 20000.5

1

dyne

/cm

2

(c) From 20th C.R.,slope=0.00041

Figure 2.18: Alongshore October to March wind stress off Peru, (a) from 1953to 1984, (between 4.5◦Sand 14.5◦S), (b) from 1946 to 1988, (between 4◦Sand14◦S, 82◦W), (c) from 1909 to 2006, (between 4◦Sand 14◦S, 82◦W) [significance: *

= P < 0.05; ** = P < 0.011], wind stress is in dyne/cm2, each mean value for October to March is assigned tothe year in which the January to March portion falls

(a) From [Bakun, 1990],slope=0.0038**

1950 1955 1960 1965 1970 1975 1980 1985

1.41.61.8

22.2

Year

dyne

/cm

2

(b) From 20th C.R.,slope=0.0077**

1920 1940 1960 1980 2000

1.5

2

Year

dyne

/cm

2

(c) From 20th C.R.,slope=0.0024**

Figure 2.19: Alongshore April to September wind stress off Peru, (a) from 1953to 1984, (between 4.5◦Sand 14.5◦S), (b) from 1946 to 1988, (between 4◦Sand14◦S, 82◦W), (c) from 1908 to 2006, (between 4◦Sand 14◦S, 82◦W) [significance: *

= P < 0.05; ** = P < 0.011, wind stress is in dyne/cm2

26

Chapter 3

Analysis of daily summervariability

3.1 Sea-land contrast

0.60.40.2

−0.2−0.4−0.6

r

(a) PC1 47.4% of total vari-ance

0.60.40.2

−0.2−0.4−0.6

r

(b) PC2 10.3% of total vari-ance

0.60.40.2

−0.2−0.4−0.6

r

(c) PC3 4.75% of total vari-ance

Figure 3.1: First three modes of principal component analysis of daily summertemperature at the USHCN stations, between 1908 and 2006

Similarly to what has been done in 2.2.2, page 14, a principal componentanalysis was performed using the correlation matrix of the daily summer max-imal temperature of the 114 USHCN stations, from June to September, from1908 to 2006. The results are shown in Figure 3.1.T dMAX PC 1 captures 47% of total daily variance and reflects coherent vari-

ations over the entire region, with all stations sharing PC loadings of the same

27

sign. The PC 1 time series is virtually identical to the unweighted mean of all114 stations records (r>0.99). T dMAX PC 2 accounts for 10% of variance andcaptures a north-south contrast. T dMAX PC 3 explains 5% and primarily reflectsa coast-interior contrast. The Principal Component Analysis of daily summerT dMAX is very similar to the one performed with summer mean values in 2.2.2.

Figure 3.1 shows the mean correlation between the PC3 of T dMAX and thedaily temperature at sigma level 0.995 from the 20th Century Reanalysis foreach year between 1908 and 2006. It displays a marked difference between theocean and the land, with the coastline as a boundary. PC3 of T dMAX is posi-tively correlated with air temperature over the ocean, and negatively correlatedwith air temperature over the land. It supports the hypothesis that this prin-cipal component has a physical meaning. The maximum absolute correlation isreached off Oregon coast (44◦N, 128◦W).

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

0.4

0.5

Figure 3.2: Mean correlation of the PC3 of summer daily T dMAX with dailytemperature, for each summer between 1908 and 2006

3.2 Interaction between wind and temperatureThe time series of PC3 of T dMAX is compared with the time series of southwardmeridional wind at sigma level 0.995 from the 20th Century Reanalysis for eachyear between 1908 and 2006. The mean correlations for each gridded point arerepresented on Figure 3.2. The correlation is rather weak. The maximum corre-lation is reached at 40◦N, 126◦W, off Northern California. An area of negativecorrelation can be noticed off the coasts of Oregon and Northern California,while an area of positive correlation covers the central and southern California.The area of minimum correlation corresponds roughly to the area of maximumsouthward wind.

To go further, for each year, we compare the time series of the PC3 ofT dMAX with the time series of the southward meridional wind at 40◦N, 126◦W.We introduce a lag between the two time series: the time series of the PC3 ofT dMAX goes from June 1stto September the 30th, and the wind time series start

28

−140 −135 −130 −125 −120 −11532

34

36

38

40

42

44

46

48

50

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

Figure 3.3: Mean correlation of the PC3 of summer daily T dMAX with dailysouthward meridional wind, for each summer between 1908 and 2006

t days later, t going from -15 to 15. We compute the correlation coefficient foreach value of t, and for each year. In Figure 3.2, the mean value for each lag isrepresented, along with the first and last quartile.

It appears that the correlation distribution is non-symmetric. The PC3of T dMAX is more correlated with the wind until a few days before, and lesscorrelated with the wind a few days after.

The time series of the PC3 of T dMAX is thus linked to the time series of thewind a few day before. However, the correlation is so low (RMAX<0.25) thatany definitive assumption is difficult.

According to this last Figure 3.2, it seems difficult to assume that the temper-ature gradient between coastal and land locations drives the upwelling-favorablewind alongshore. Rather than a response of the temperature to the wind along-shore, wind evolutions seems to antedate temperature gradient fluctuations.

29

−15 −10 −5 0 5 10 150

0.05

0.1

0.15

0.2

0.25

0.3

Figure 3.4: Correlation between PC3 of T dMAX and meridional wind t dayslater. For each summer, the correlation between the PC3 of T dMAX time series from June1stand September 30þand the time series of southward meridional wind, with a lag of t daysis computed. Are plotted the mean value for each lag, and the first and last quartile of thedistribution of correlation coefficient.

30

Chapter 4

Discussion

Several trend have been exhibited in the atmospheric fields over the U.S. Westcoast area. The sea surface temperature as well as the land temperature haveincreased during the 20th Century. The inversion has lost strength off centraland southern California, whereas the mean pressure has decreased. Over land,the temperature at the coastal locations has increased faster than at inlandlocations, leading to a decrease of the temperature gradient between coast andland.

We can try to account for these trends with a simple model. The North Pa-cific High seems to have gradually retracted, leading to a decrease of pressure offCalifornian coasts. The subsidence of warm air over the marine boundary layeris thus weaker, and the inversion strength decreases. The marine boundary isthicker, and when the inversion is higher than coastal topography, marine air candrip over the coastal ranges, carrying with it moisture and cloudiness. Cloudsover land reduces the incoming solar radiation amount, producing cool condi-tions inland, while warmer and dryer conditions predominates in the coastalarea. It accounts for the stronger increase in temperature for coastal locationsthan for inland locations, and thus for the decrease in temperature gradient. Thesea surface temperature increase can be explained both by this phenomenon ofincreased coastal temperature, as well as by global warming. Even if the up-welling has increased, which is not clear, its contribution in cold water from thedepths is not enough to oppose the global increase trend in temperature.

Such a model have been recognized by [Fosberg and Schroeder, 1966] ondaily time scales, and by [Johnstone and Dawson, 2010] to explain the interan-nual variability.

This scenario is not perfect. As the marine boundary layer is thicker andthicker, the alongshore wind should decrease. However, in several studies ([Bakun, 1990,Schwing and Mendelssohn, 1997, Garcia-Reyes and Largier, 2010]) an increaseof the alongshore wind stress has been observed. Increase in alongshore windstress is part of an opposite scenario, which has been documented on daily[Fosberg and Schroeder, 1966] and interrannual [Johnstone and Dawson, 2010]time scales. When the Pacific high is extended and penetrates into Oregon andWashington, the subsidence is strong over the marine boundary layer, which isthus shallow and can’t drip over the coastal topography. Cool marine air andclouds tend to be sequestered at the coastline, evolving into fog, while clear skiesand compressional adiabatic warming prevail over the interior. The alongshore

31

wind is strong, due to the thinner marine boundary layer. Such a behaviorcan be observed for August, 15th 1962 [Fosberg and Schroeder, 1966], or for thewhole year 1951 [Johnstone and Dawson, 2010].

Notes1Indicated significance level are taken directly from standard tables of the Student’s t

distribution,without adjustment for residual autocorrelation.

32

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[Bakun, 1990] Bakun, A. (1990). Global climate change and intensification ofcoastal ocean upwelling. Science, 247(4939):198–201.

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[Botsford et al., 2006] Botsford, L., Lawrence, C., Dever, E., Hastings, A., andLargier, J. (2006). Effects of variable winds on biological productivity oncontinental shelves in coastal upwelling systems. Deep Sea Research Part II:Topical Studies in Oceanography, 53(25-26):3116–3140.

[Capet et al., 2004] Capet, X., Marchesiello, P., and McWilliams, J. (2004).Upwelling response to coastal wind profiles. Geophys. Res. Lett, 31:13.

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[Johnstone and Dawson, 2010] Johnstone, J. and Dawson, T. (2010). Climaticcontext and ecological implications of summer fog decline in the coast redwoodregion. Proceedings of the National Academy of Sciences, 107(10):4533.

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34

List of Figures

1.1 Mean summer sea level pressure between 1908 and 2006 (datafrom 20th Century Reanalysis dataset) . . . . . . . . . . . . . . . 4

1.2 Average summer cross section from San Francisco to Honolulu(from [Neiburger et al., 1961]) . . . . . . . . . . . . . . . . . . . . 4

1.3 Conceptual model of average lower atmosphere over eastern NorthPacific during periods of persistent south and southeastward windsin summer (from [Beardsley et al., 1987]) . . . . . . . . . . . . . 5

1.4 Conceptual model of average lower atmosphere over the nearshorezone during (top) night and (bottom) day. (from [Beardsley et al., 1987]) 5

1.5 A conceptual diagram of the coastal upwelling process [from www.nwfsc.noaa.gov] 6

2.1 Correlation of mean summer (JJAS) temperature between the20thCentury Reanalysis Data and the USHCN Data, from 1908to 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2 Correlation of mean summer (JJAS) meridional wind between the20thCentury Reanalysis Data and the NDBC Data, from 1908 to2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.3 Mean linear trend of mean NDBC summer meridional wind, from1983 to 2009. The ? represent the stations for which no linear trend canbe observed with a confidence level higher than 95% (P<0.051) . . . . . . 12

2.4 Mean linear trend of mean 20th Century Reanalysis summer south-ward meridional wind at sigma level 0.995, from 1908 to 2006.Only are represented the grid points where the sign of the linear trend issure at the 95% confidence level (P<0.051) . . . . . . . . . . . . . . . . 13

2.5 Mean linear trend of mean USHCN summer average temperature,from 1908 to 2006. Only are plotted the stations for which the sign ofthe linear trend is sure at the 95% confidence level (P<0.05 1) . . . . . . 13

2.6 The three first principal component of the mean summer air tem-perature from the 114 western U.S. USHCN stations . . . . . . . 14

2.7 Map of United States West Coast. The stations of Orland and ofSan Luis Obispo are represented . . . . . . . . . . . . . . . . . . 15

2.8 Mean linear trend of mean 20th Century Reanalysis summer tem-perature at sigma level 0.995, from 1908 to 2006. The grid pointswhere the sign of the linear trend is not sure at the 95% confidence level(P<0.051) are represented in green . . . . . . . . . . . . . . . . . . . . 16

2.9 Mean sea surface temperature at (32◦N,122◦W) and the PC3 ofTMAX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

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2.10 Mean linear trend of mean 20th Century Reanalysis summer pres-sure at sigma level 0.995, from 1908 to 2006. The grid points wherethe sign of the linear trend is not sure at the 95% confidence level (P<0.051)are represented in green. The units of the colorbar are Pa/an . . . . . . . 17

2.11 Optional caption for list of figures . . . . . . . . . . . . . . . . . 182.12 Temperature difference between 850 mbar and 950 mbar at (32◦N,116◦W),

and TMAX PC3 (inverted) . . . . . . . . . . . . . . . . . . . . . . 202.13 Correlation between mean summer southward meridional wind

and the PC3 of TMAX . . . . . . . . . . . . . . . . . . . . . . . . 212.14 Results of the Singular Value Decomposition of the mean summer

(JJAS) temperature from the 114 USHCN stations and of thesouthward meridional wind, between 1908 and 2006 . . . . . . . 23

2.15 Alongshore April to September wind stress off California, (a) from1946 to 1988, (39◦N,125◦W), (b) from 1946 to 1988, (38◦N,124◦W),(c) from 1908 to 2006, (38◦N,124◦W) [significance: * = P < 0.05; ** = P <

0.011], wind stress is in dyne/cm2 . . . . . . . . . . . . . . . . . . . . . . . 252.16 Alongshore April to September wind stress off Spain, (a) from

1946 to 1981, (43◦N), (b) from 1946 to 1988, (42◦N,10◦W), (c)from 1908 to 2006, (42◦N,10◦W) [significance: * = P < 0.05; ** = P < 0.011],

wind stress is in dyne/cm2 . . . . . . . . . . . . . . . . . . . . . . . . . . 252.17 Alongshore annual wind stress off Morocco, (a) from 1946 to 1981,

(28◦N), (b) from 1946 to 1988, (28◦N,22◦W), (c) from 1908 to2006, (28◦N,22◦W) [significance: * = P < 0.05; ** = P < 0.011],wind stress is in dyne/cm2 . . . . . . . . . . . . . . . . . . . . . . 25

2.18 Alongshore October to March wind stress off Peru, (a) from 1953to 1984, (between 4.5◦Sand 14.5◦S), (b) from 1946 to 1988, (be-tween 4◦Sand 14◦S, 82◦W), (c) from 1909 to 2006, (between4◦Sand 14◦S, 82◦W) [significance: * = P < 0.05; ** = P < 0.011], wind stress

is in dyne/cm2, each mean value for October to March is assigned to the year in which the

January to March portion falls . . . . . . . . . . . . . . . . . . . . . . . . 262.19 Alongshore April to September wind stress off Peru, (a) from

1953 to 1984, (between 4.5◦Sand 14.5◦S), (b) from 1946 to 1988,(between 4◦Sand 14◦S, 82◦W), (c) from 1908 to 2006, (between4◦Sand 14◦S, 82◦W) [significance: * = P < 0.05; ** = P < 0.011, wind stress is in

dyne/cm2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.1 First three modes of principal component analysis of daily sum-mer temperature at the USHCN stations, between 1908 and 2006 27

3.2 Mean correlation of the PC3 of summer daily T dMAX with dailytemperature, for each summer between 1908 and 2006 . . . . . . 28

3.3 Mean correlation of the PC3 of summer daily T dMAX with dailysouthward meridional wind, for each summer between 1908 and2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.4 Correlation between PC3 of T dMAX and meridional wind t dayslater. For each summer, the correlation between the PC3 of T dMAX time se-ries from June 1stand September 30þand the time series of southward merid-ional wind, with a lag of t days is computed. Are plotted the mean valuefor each lag, and the first and last quartile of the distribution of correlationcoefficient. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

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